| Literature DB >> 33398191 |
Dylan Bannon1, Erick Moen2, Morgan Schwartz2, Enrico Borba1, Takamasa Kudo3, Noah Greenwald4, Vibha Vijayakumar1, Brian Chang2, Edward Pao2, Erik Osterman5, William Graf2, David Van Valen6.
Abstract
Deep learning is transforming the analysis of biological images, but applying these models to large datasets remains challenging. Here we describe the DeepCell Kiosk, cloud-native software that dynamically scales deep learning workflows to accommodate large imaging datasets. To demonstrate the scalability and affordability of this software, we identified cell nuclei in 106 1-megapixel images in ~5.5 h for ~US$250, with a cost below US$100 achievable depending on cluster configuration. The DeepCell Kiosk can be downloaded at https://github.com/vanvalenlab/kiosk-console ; a persistent deployment is available at https://deepcell.org/ .Entities:
Mesh:
Year: 2021 PMID: 33398191 PMCID: PMC8759612 DOI: 10.1038/s41592-020-01023-0
Source DB: PubMed Journal: Nat Methods ISSN: 1548-7091 Impact factor: 47.990